Shifting Views on Cancer Pain Management: A Systematic Review and Network Meta-Analysis.

CONTEXT: Strong opioids are the cornerstone in the treatment of cancer-related pain. OBJECTIVES: This study aims to compare analgesic effectiveness of different strong opioids for the treatment of cancer-related pain. METHODS: PubMed and Embase were searched for RCTs that compared strong opioids for treatment of cancer-related pain against one another. A network meta-analysis was conducted and the related Surface Under the Cumulative RAnking (SUCRA)-based treatment ranks were calculated. Primary outcome was pain intensity (numerical rating scale (NRS)) and/or the percentage of patients with ≥50% pain reduction, after 1 and 2-4 weeks. RESULTS: Sixteen RCTs (1813 patients) were included. Methadone showed, with a high certainty of evidence, increased ORs for treatment success at 1 week, compared with morphine, buprenorphine, fentanyl, and oxycodone, range 3.230-36.833. Methadone had the highest likelihood to be the treatment of preference (ToP) (SUCRA 0.9720). For fentanyl, ORs were lower, however significant and with high certainty. After 2-4 weeks, methadone again showed the highest likelihood for ToP, however, with moderate certainty and nonsignificant ORs. The combination of morphine/methadone, compared with morphine, buprenorphine, fentanyl, hydromorphone, methadone, and oxycodone achieved a treatment effect of mean NRS difference after 2-4 weeks between -1.100 and -1.528 and had the highest likelihood for ToP. CONCLUSION: The results suggest that methadone possibly deserves further promotion as first-line treatment for the treatment of cancer-related pain.

Finding predictors for successful opioid response in cancer patients: An analysis of data from four randomized controlled trials.

CONTEXT: There is no consensus on which "strong" (or step 3 WHO analgesic ladder) opioid to prescribe to a particular patient with cancer-related pain. A better understanding of opioid and patient characteristics on treatment response will contribute to a more personalized opioid treatment. OBJECTIVES: Assessment of potential predictors for successful opioid treatment response in patients with cancer pain. METHODS: An international partnership between four cancer pain research groups resulted in a combined individual-level database from four relevant randomized controlled trials (RCTs; n = 881). Together, these RCTs investigated the short-term (1 week) and medium-term (4 or 5 weeks) treatment responses for morphine, buprenorphine, methadone, oxycodone, and fentanyl. Candidate predictors for treatment response were sex, age, pain type, pain duration, depression, anxiety, Karnofsky performance score, opioid type, and use of anti-neuropathic drug. RESULTS: Opioid type and pain type were found statistically significant predictors of short-term treatment success. Sex, age, pain type, anxiety, and opioid type were statistically, significantly associated with medium-term treatment success. However, these models showed low discriminative power. CONCLUSION: Fentanyl and methadone, and mixed pain were found to be statistically significant predictors of treatment success in patients with cancer-related pain. With the predictors currently assessed our data did not allow for the creation of a clinical prediction model with good discriminative power. Additional - unrevealed - predictors are necessary to develop a future prediction model.

Reasons and predictors of non-participation in a personalized digital prehabilitation care trial for patients undergoing elective cardiothoracic surgery.

OBJECTIVES: Prehabilitation through a digital platform could preoperatively improve the physical and mental fitness of patients undergoing cardiothoracic surgery, thereby improving treatment outcomes. This study aimed to describe the reasons and predictors of non-participation in a personalized digital prehabilitation care trial (Digital Cardiac Counseling randomized controlled trial) for patients undergoing elective cardiothoracic surgery. METHODS: Adult patients scheduled for elective cardiothoracic surgery at the Maastricht University Medical Center+ were approached to participate in a digital prehabilitation care trial, in which patients were informed about their care pathway, monitored for symptom progression and screened for preoperative modifiable risk factors. Baseline characteristics of all eligible patients and reasons of non-participation were registered prospectively. Predictors of non-participation were determined using logistic regression. RESULTS: Between May 2020 and August 2022, 815 patients were eligible for participation; 421 (52%) did not participate in the personalized digital prehabilitation care trial. Reasons for non-participation were 'lack of internet access or insufficient digital skills' (32%), 'wishing no participation' (39%) and 'other reasons' (30%; e.g. vision or hearing impairments, analphabetism, language barriers). Independent predictors of non-participation were age [odds ratio (OR) 1.024 (1.003-1.046), P = 0.024], socioeconomic status [OR 0.267 (0.133-0.536), P < 0.001], current smoker [OR 1.823 (1.124-2.954), P = 0.015] and EuroSCORE II [OR 1.160 (1.042-1.292), P = 0.007]. CONCLUSIONS: Half of the eligible patients did not participate in a personalized digital prehabilitation care trial. Non-participants were vulnerable patients, with a more unfavourable risk profile and more modifiable risk factors, who could potentially benefit the most from prehabilitation.

Digital Health Solutions to Reduce the Burden of Atherosclerotic Cardiovascular Disease Proposed by the CARRIER Consortium.

Digital health is a promising tool to support people with an elevated risk for atherosclerotic cardiovascular disease (ASCVD) and patients with an established disease to improve cardiovascular outcomes. Many digital health initiatives have been developed and employed. However, barriers to their large-scale implementation have remained. This paper focuses on these barriers and presents solutions as proposed by the Dutch CARRIER (ie, Coronary ARtery disease: Risk estimations and Interventions for prevention and EaRly detection) consortium. We will focus in 4 sections on the following: (1) the development process of an eHealth solution that will include design thinking and cocreation with relevant stakeholders; (2) the modeling approach for two clinical prediction models (CPMs) to identify people at risk of developing ASCVD and to guide interventions; (3) description of a federated data infrastructure to train the CPMs and to provide the eHealth solution with relevant data; and (4) discussion of an ethical and legal framework for responsible data handling in health care. The Dutch CARRIER consortium consists of a collaboration between experts in the fields of eHealth development, ASCVD, public health, big data, as well as ethics and law. The consortium focuses on reducing the burden of ASCVD. We believe the future of health care is data driven and supported by digital health. Therefore, we hope that our research will not only facilitate CARRIER consortium but may also facilitate other future health care initiatives.

Last-minute cancellation of adult patients scheduled for cardiothoracic surgery in a large Dutch tertiary care centre.

OBJECTIVES: Unanticipated cancellation of a surgical procedure is a common problem, causing distress to the patient and increases in healthcare costs. However, limited evidence exists on the effects of last-minute cancellations of cardiothoracic surgical procedures in particular. The goal of this study was to gain insight into the prevalence of and the reasons for last-minute cancellations and to examine whether cancellation is associated with adverse medical outcomes. METHODS: Patients who were scheduled for elective cardiothoracic surgical procedures between January 2017 and June 2019 were evaluated. The reasons for the cancellations were assigned to the categories medically related or process related. We examined the differences in patient characteristics between those designated as no cancellation, medically related cancellations and process-related cancellations. Lastly, we examined the outcomes of patients who experienced a last-minute cancellation of a scheduled operation. RESULTS: A total of 2111 patients were included; of these, 301 (14.3%) had last-minute cancellations. In 78 (26%) cases, the cancellations were attributable to medical reasons (e.g. infection, comorbidities); 215 (71%) of the cancellations were process related (e.g. another patient in more urgent need of surgery, lack of staff). Almost 99% of the operations with a process-related cancellation were rescheduled compared to only 71.8% of the medically related cancelled operations (P < 0.001). Patients with a medically related cancellation had significantly higher 1-year mortality than patients who had no cancellation (unadjusted hazard ratio 2.50; 95% confidence interval, 1.30-4.78; P = 0.006); after adjustment for the EuroSCORE II, this effect remained significant. CONCLUSIONS: Last-minute cancellations were commonly seen in our cohort, and the reasons for cancellation were significantly related to adverse medical outcomes.

Uncovering the heterogeneity of disease impact in axial spondyloarthritis: bivariate trajectories of disease activity and quality of life.

OBJECTIVE: The goal of managing axial spondyloarthritis (axSpA) is to improve and maintain patients' health-related quality of life (HRQoL), mainly through targeting towards low disease activity. Here, we aim to gain insight into the joint evolution of HRQoL and disease activity by identifying and characterising latent subgroups of patients with longstanding disease displaying similar trajectories throughout 8 years of follow-up. METHODS: Data from Outcome in Ankylosing Spondylitis (AS) International Study (n=161) and Groningen Leeuwarden AS cohort (n=264) were used. Biennially, HRQoL was assessed by AS Quality of Life (ASQoL) and disease activity by AS Disease Activity Score-C reactive protein (ASDAS-CRP). Bivariate trajectories of these outcomes were estimated by group-based trajectory modelling. Next, trajectories were profiled by comparing the latent groups with respect to baseline factors using analysis of variance and χ² test. RESULTS: Five bivariate trajectories were distinguished, in which ASQoL and ASDAS-CRP were tightly linked: (t1) low impact of disease; (t2) moderate impact; (t3) high impact with major improvement; (t4) high impact with some improvement; (t5) very high impact. Profiling revealed, for example, that (t1) was characterised by male gender and Human Leucocyte Antigen B27 positivity; (t3) by younger age, shorter symptom duration and biological intake and (t5) by the highest proportion of females. CONCLUSIONS: We identified five bivariate trajectories of HRQoL and disease activity demonstrating a clear mutual relationship. The profiles revealed that both individual-related and disease-related features define the type of disease course in respect to HRQoL and disease activity in axSpA. This may provide clinicians insight into the differences among patients and help in the management of the disease.